Autonomous mower navigation system and method
A method for autonomous mower navigation includes receiving a return-to-zero encoded signal including a pseudo-random sequence, transforming the received signal to a non-return-to-zero representation, digitally sampling the non-return-to-zero signal representation in a time domain, filtering the sampled signal utilizing a reference data array based on the return-to-zero encoded signal to produce a filter output, and determining a location of the autonomous mower relative to a defined work area based on an evaluation of the filter output.
1. A computer implemented method for autonomous mower navigation, comprising:
receiving a return-to-zero encoded signal including a neutral condition between bits and comprising at least one pseudo-random sequence, wherein the neutral condition comprises a value halfway between a condition representing a 1 bit and a condition representing a 0 bit;
transforming the received signal to a non-return-to-zero phase-shift keyed representation, wherein the non-return-to-zero phase-shift keyed representation comprises a binary code in which binary 0's are represented by a negative voltage and binary 1's are represented by a positive voltage, and wherein the non-return-to-zero phase-shift keyed representation does not include a neutral condition;
digitally sampling the non-return-to-zero signal representation in a time domain;
filtering the sampled signal utilizing a reference data array based on the return-to-zero encoded signal to produce a filter output; and
determining a location of the autonomous mower relative to a defined work area based on an evaluation of the filter output.
2. The method for autonomous mower navigation of claim 1 , comprising receiving a plurality of return-to-zero encoded signals each signal comprising at least one pseudo-random sequence, wherein the pseudo-random sequences comprise a set of sequences having good auto-correlation properties and a low cross-correlation with other sequences in the set.
3. The method for autonomous mower navigation of claim 2 , wherein at least one return-to-zero encoded signal is associated with the defined work area, and at least one return-to-zero encoded signal is associated with a guide wire.
4. The method for autonomous mower navigation of claim 1 , wherein the pseudo-random sequence comprises at least one of Barker Codes, Gold Codes, Kasami Codes, Walsh Hadamard Codes, and/or similarly derived codes.
5. The method for autonomous mower navigation of claim 1 , wherein filtering the sampled signal comprises utilizing a time domain matched filter based on the non-return-to-zero representation to produce at least one correlation maxima and/or at least one correlation minima.
6. The method for autonomous mower navigation of claim 5 , wherein the at least one correlation maxima and/or at least one correlation minima comprises a single correlation maxima and/or a single correlation minima.
7. The method for autonomous mower navigation of claim 1 , comprising
converting the digitally sampled signal from a time domain to a representation in a frequency domain; and
wherein filtering the sampled signal comprises computing a cross-correlation by multiplying the frequency domain representation by the reference data array to obtain a product, and performing an inverse fast Fourier transform on the product to produce at least one correlation maxima and/or at least one correlation minima.
8. The method for autonomous mower navigation of claim 7 , wherein the at least one correlation maxima and/or at least one correlation minima comprises a single correlation maxima and/or a single correlation minima.
9. The method for autonomous mower navigation of claim 1 , wherein the evaluation comprises one or more of a count of correlation minima and/or maxima, a ratio of correlation minima and/or maxima, and a frequency of correlation minima and/or maxima, occurring within an acquisition period.
10. The method for autonomous mower navigation of claim 1 , wherein the evaluation comprises one or more of a distribution of correlation minima and/or maxima, and a threshold value of correlation minima and/or maxima, occurring within an acquisition period.
11. The method for autonomous mower navigation of claim 1 , wherein the reference data array comprises a discrete time domain representation of a model non-return-to-zero received signal.
12. The method for autonomous mower navigation of claim 1 , wherein the reference data array comprises a discrete frequency domain transformation of a discrete time domain representation of a model received signal.
13. The method for autonomous mower navigation of claim 1 , wherein the reference data array comprises a discrete filtered frequency domain transformation of a discrete time domain representation of a model received signal.
14. A system for autonomous mower navigation, comprising:
at least one inductive sensor for receiving a return-to-zero encoded signal comprising at least one pseudo-random sequence transmitted over a wire defining a work area, wherein the return-to-zero encoded signal includes a neutral condition between bits, the neutral condition comprising a value halfway between a condition representing a 1 bit and a condition representing a 0 bit;
a processing component in communication with the at least one sensor and for receiving the signal data, wherein the processing component is configured to
i. transform the signal data to a non-return-to-zero phase-shift keyed representation of the signal data, wherein the non-return-to-zero phase-shift keyed representation comprises a binary code in which binary 0's are represented by a negative voltage and binary 1's are represented by a positive voltage, and wherein the non-return-to-zero phase-shift keyed representation does not include a neutral condition;
ii. digitally sample the non-return-to-zero signal representation in a time domain; and
a filter in communication with the processing component for filtering the sampled signal utilizing a reference data array based on the return-to-zero encoded signal to produce a filter output, wherein the processing component receives the filter output and is configured to determine a location of the autonomous mower relative to the defined work area based on an evaluation of the filter output.
15. The system for autonomous mower navigation of claim 14 , comprising a plurality of return-to-zero encoded signals each signal comprising at least one pseudo-random sequence, wherein the pseudo-random sequences comprise a set of sequences having good auto-correlation properties and a low cross-correlation with other sequences in the set.
16. The system for autonomous mower navigation of claim 15 , wherein at least one return-to-zero encoded signal is associated with the defined work area, and at least one return-to-zero encoded signal is associated with a guide wire.
17. The system for autonomous mower navigation of claim 14 , wherein the pseudo-random sequence comprises at least one of Barker Codes, Gold Codes, Kasami Codes, Walsh Hadamard Codes, and/or similarly derived codes.
18. The system for autonomous mower navigation of claim 14 , wherein the filter comprises a time domain matched filter based on the non-return-to-zero representation, and the filter output comprises at least one correlation maxima and/or at least one correlation minima.
19. The system for autonomous mower navigation of claim 18 , wherein the at least one correlation maxima and/or at least one correlation minima comprises a single correlation maxima and/or a single correlation minima.
20. The system for autonomous mower navigation of claim 14 , wherein the digitally sampled signal is converted from a time domain to a representation in a frequency domain; and
wherein the filter is configured to calculate a cross-correlation by multiplying the frequency domain representation by the reference data array to obtain a product, and performing an inverse fast Fourier transform on the product to produce at least one correlation maxima and/or at least one correlation minima.
21. The system for autonomous mower navigation of claim 20 , wherein the at least one correlation maxima and/or at least one correlation minima comprises a single correlation maxima and/or a single correlation minima.
22. The system for autonomous mower navigation of claim 14 , wherein the evaluation comprises one or more of a count of correlation minima and/or maxima, a ratio of correlation minima and/or maxima, and a frequency of correlation minima and/or maxima, occurring within an acquisition period.
23. The system for autonomous mower navigation of claim 14 , wherein the evaluation comprises one or more of a distribution of correlation minima and/or maxima, and a threshold value of correlation minima and/or maxima, occurring within an acquisition period.
24. The system for autonomous mower navigation of claim 14 , wherein the reference data array comprises a discrete time domain representation of a model non-return-to-zero received signal.
25. The system for autonomous mower navigation of claim 14 , wherein the reference data array comprises a discrete frequency domain transformation of a discrete time domain representation of a model received signal.
26. The system for autonomous mower navigation of claim 14 , wherein the reference data array comprises a discrete filtered frequency domain transformation of a discrete time domain representation of a model received signal.